In DLMtool/DLMtool: Data-Limited Methods Toolkit

if (params$tabs) {
  cat('### Historical Effort {.tabset .tabset-fade .tabset-pills}' )
} else {
  cat('### Historical Effort')
}

dd <- params$Pars$M_ageArray %>% dim()
nsim <- dd[1]
maxage <- dd[2]

nsamp <- length(params$its)
nyears <- params$nyears
proyears <- params$proyears

Sampled Parameters

Histograms of r nsim simulations of inter-annual variability in historical fishing mortality (Esd), with vertical colored lines indicating r nsamp randomly drawn values used in the time-series plot:

par(mfrow=c(1,1))

hist2(Pars$Esd, col=params$plotPars$col, axes=params$plotPars$axes, main="Esd", breaks=params$plotPars$breaks)
abline(v=Pars$Esd[params$its], col=1:nsamp, lwd=params$plotPars$lwd)
axis(side=1)

Time-Series

Time-series plot showing r nsamp trends in historical fishing mortality (OM@EffUpper and OM@EffLower or OM@cpars$Find):

par(mfrow=c(1,1))


CurrentYr <- Pars$CurrentYr
histYr <- (CurrentYr-nyears+1):CurrentYr
futYr <- (CurrentYr+1):(CurrentYr+proyears)
Years <- histYr

matplot(Years, t(Pars$Find[params$its,]), type="l", lwd=params$plotPars$lwd, bty="l", lty=1,
        ylab="Relative F", xlab="Year")